Choosing to click either the Import or Direct Query box is one of the first decisions you’ll have to make as a Power BI developer. The decision is dependent on your report, but you should also have a strategy in place on how to use both options.
This guide gives more insight into the Power BI import vs direct query debate. It shows you what the Power BI import is, what direct query in Power BI is, the key differences between the Power BI direct query vs import, and its advantages and disadvantages.
First…
With the Import method, data imported into the Power BI is stored in a compressed in-memory column store. This method comes in handy when dealing with smaller data sets or when the data is updated infrequently.
Users who use the Import method can create complex Power BI data models, create visualizations and reports based on the imported data, and perform advanced calculations using the Data Analysis Expressions (DAX) language.
When using the DirectQuery method, data stays in the source system and it’s queried directly by Power BI. This method comes in handy when you’re handling large Power BI datasets or when the data is frequently updated.
Users who use DirectQuery can create data models that span multiple tables or even multiple data sources and perform real-time data analysis of the source data. Since the data is not imported into Power BI, you’ll have no need for manual data refresh. After all, the data is always up-to-date.
Here are steps to help you manually import Analytics data through Power BI.
Click “Local File.”
Choose the file to upload and click “Open.” Next, click “Upload” under “Upload your Excel file to Power BI.”
You’ll see the “Your file has been uploaded” message.
First, navigate to the “Home” section of the Power BI Desktop ribbon, and select “Get data.” After that, select a data source that DirectQuery supports like “SQL Server.”
In the dialog box, under the “Data connectivity mode,” select “DirectQuery.”
Stage 1: Logging in to Power BI
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Q1 | Samsung | 27.69 |
Q1 | Apple | 28.45 |
Q1 | Xiaomi | 11.8 |
Q1 | Huawei | 6.53 |
Q1 | Oppo | 5.3 |
Q1 | Vivo | 4.19 |
Q2 | Samsung | 28.14 |
Q2 | Apple | 27.58 |
Q2 | Xiaomi | 12.62 |
Q2 | Huawei | 6.17 |
Q2 | Oppo | 5.5 |
Q2 | Vivo | 4.21 |
Q3 | Samsung | 28.45 |
Q3 | Apple | 27.71 |
Q3 | Xiaomi | 12.9 |
Q3 | Huawei | 6 |
Q3 | Oppo | 5.29 |
Q3 | Vivo | 4.17 |
Q4 | Samsung | 27.97 |
Q4 | Apple | 27.62 |
Q4 | Xiaomi | 12.68 |
Q4 | Huawei | 5.17 |
Q4 | Oppo | 6.07 |
Q4 | Vivo | 4.66 |
Yes, you can change from DirectQuery to Import in Power BI by modifying the data source settings within the report’s data model. It involves data importation into Power BI’s internal storage.
Two benefits of using DirectQuery over Import in Power BI are real-time data access that ensures up-to-date insights, and avoiding data duplication. Avoiding data duplication helps reduce storage requirements and ascertain data integrity.
Yes, measures can be created in DirectQuery mode in Power BI. It’s important to know that complex calculations may impact performance due to real-time querying.
When it comes to the Power BI Import vs Direct Query debate, the major difference is in where the data resides. Import imports data into Power BI, while DirectQuery connects to the source in real-time. The data location affects the performance, scalability, and data freshness. It also impacts decision-making and analysis.
Power BI Import gives room for extensive data transformation and modeling capabilities when data is imported. Users can apply various transformations, define relationships between tables, and create calculated columns. However, data transformations are limited in DirectQuery mode since the data resides in the source system. There are cases where transformations have to be performed directly in the source system (or through Power Query in Power BI).
By following the steps in this guide, you’ll become a proficient Power BI user and will be able to create more engaging and interactive visualizations.